This data set contains 1.0 Degree UK MetOffice forecast imagery. The forecast products are available at 6 hourly intervals out to 36 hours and 12 hourly intervals from 36 to 120 hours. The products include a variety of wind, height, moisture, shear, divergence, potential temperature, and vorticity forecast products from the operational UK MetOffice model.

Ten operational Numerical Weather Prediction (NWP) and two data assimilation centers are currently contributing analysis/assimilation and forecast model products from global and regional NWP suites, including both operational and reanalysis systems to this component of CEOP. The contributing centers include:

BoM: Bureau of Meteorology CPTEC: Centro de Previsao de Tempo e Estudos Climaticos ECMWF: European Centre for Medium-Range Weather Forecasts ECPC: Experimental Climate Prediction Center EMC: EPSON Meteo Center (Centro EPSON Meteo) GLDAS: Global Land Data Assimilation System GMAO: NASA Global Modeling and Assimilation Office JMA: Japan Meteorological Agency MSC: Meteorological Service Canada NCEP: National Centers for Environmental Prediction NCMRWF: National Center for Medium Range Weather Forecasting UKMO: UK Met Office The Max-Planck Institute for Meteorology (MPIM) in coordination with the ICSU World Data Center for Climate (WDCC) in Hamburg, Germany was designated as the CEOP model output archive center. The WDCC is administered by the Model and Data Group (M&D) at MPIM and the German Climate Computing Center (DKRZ).

To assist with the organization of this activity during the Coordinated Enhanced Observing Period ('CEOP'), a Model Output Management Document was drafted as a guide for the participating centers to use in setting up their processes for meeting their commitments to 'CEOP'. The Guidance Document addressed the two issues of (1) the model output variables requested by 'CEOP' and (2) the two types of requested model output, namely global gridded (in GRIB format) and site-specific Model Output Location Time Series (MOLTS) at each of the 'CEOP' Reference Sites.

A new version of the Guidance Document will be compiled that clarifies what model output data will be generated by the NWP Centers and Groups contributing to the model output component of Coordinated Energy and Water Cycle Observations Project (CEOP) and how they will interface/transfer the data that will be handled and retained at the WDCC. The issues covered in the document will include: (1) global versus regional products; (2) desired assimilation output; Interval and length of free-running forecasts; (3) Operational versus reanalysis data; (4) the CEOP schedule/archive periods; (5) the number and locations of MOLTS sites; and (6) the homogenizing of the model output and metadata formats (i.e. standard parameters).

Results up to this point in the CEOP model output generation effort make it clear that the transfer aspect of the data handling effort has been progressing well. Data from all twelve Centers participating in CEOP have been received at the data archive center and has either been placed into the database at the Hamburg facility, or is in the process of being entered into the database. The current data holdings in the MPIM archive can be viewed http://www.mad.zmaw.de/fileadmin/extern/wdc/ceop/Data_timeline_L_12.pdf.

This data set includes a subset of analysis products from the UK Met Office Global Unified Model over the HIGHWAY region around Lake Victoria. The analysis is run four times per day at 00, 06, 12, and 18 UTC at a horizontal resolution of approximately 4.4km and with 80 vertical levels. The following fields are included: three hourly precipitation amount, instantaneous precipitation rate, surface and vertical profiles (200, 500, 700, and 850mb) of wind components, temperature, and relative humidity and surface dew point temperature. The data are in NetCDF format.

This dataset contains standard assimilated data concerning stratospheric temperature, geopotential height and wind components produced by the Stratospheric Data Assimilation System at the UK Met Office. Data is provided from 1991 to 2022.

The data assimilation system is a development of the scheme used at the Met Office for operational weather forecasting, which has been extended to cover the stratosphere. The primary product is a daily analysis (at 1200 UTC) which is produced using operational observations only. For short periods of particular interest the analyses are available at 6-hourly intervals. Assimilation experiments using UARS (Upper Atmosphere Research Satellite) data in addition to operational meteorological observations have been carried out for limited periods.

The global model producing this data was updated on July 11th 2017. Data from this date has an increased resolution of N1280L70: 2560 latitude x1920 longitude and vertical 70 levels (model top 80 km), see the documentation for full details.

The United Kingdom Composite, Surface Rain Rate Estimate is an international radar composite produced by Met Office (UK). This is a composite, radar reflectivity derived, surface rain rate estimate product in HDF5 code from stations covering the United Kingdom.

The Greenland Flow Distortion EXperiment investigates the role of Greenland in defining the structure and the predictability of both local and downstream weather systems, through a programme of aircraft-based observation and numerical modelling. The Greenland Flow Distortion Experiment (GFDex) will provide some of the first detailed in situ observations of the intense atmospheric forcing events that are thought to be important in modifying the ocean in this area (but are presently poorly understood): namely tip jets, barrier winds and mesoscale cyclones. The dataset contains Met Office forecast products.

This dataset contains the annual index of wind-driven rain (sum of all wind-driven rain spells in each year) derived from the UK Climate Projections (UKCP18) for a range of future global warming levels provided on a 5 km British National Grid (BNG). The annual index is calculated for eight wall orientations corresponding to the cardinal and ordinal points of the compass.

Wind-driven rain occurs when falling rain is blown by a horizontal wind so that it falls diagonally towards the ground. The annual index of wind-driven rain is the sum of all wind-driven rain spells for a given wall orientation and time period. It’s measured as the volume of rain blown from a given direction in the absence of any obstructions, with units of litres per square metre per year.

Wind-driven rain is calculated from hourly weather and climate data using an industry-standard formula from ISO 15927–3:2009, which is based on the product of wind speed and rainfall totals. Wind-driven rain is only calculated if the wind would strike a given wall orientation. A wind-driven rain spell is defined as a wet period separated by at least 96 hours with little or no rain (below a threshold of 0.001 litres per m2 per hour).

The annual index of wind-driven rain is calculated for a baseline (historical) period of 1981-2000 (corresponding to 0.61°C warming) and for global warming levels of 2.0°C and 4.0°C above the pre-industrial period (defined as 1850-1900). The warming between the pre-industrial period and baseline is the average value from six datasets of global mean temperatures available on the Met Office Climate Dashboard: https://climate.metoffice.cloud/dashboard.html.

The magnitudes of 1 in 3 year wind-driven rain spells (i.e. wet spells that would be expected to occur, on average, once every three years) are used to divide the UK into four zones in Approved Document C of the buildings regulations. The magnitudes of 1 in 3 year wind-driven rain spells were calculated for the baseline period (1981-2000) and 20-year periods corresponding to 2°C and 4°C of warming. The magnitudes of all wet spells (here, sum of hourly values of the wind-driven rain metric, I) were calculated, and the largest wet spell in each year was found (in the accompanying report, the magnitude of a wet spell is given the symbol Is' ["Is prime"] and has units of litres per metre-squared per spell). For each time period, the largest spells in all years and ensemble members were pooled together. A Gumbel distribution was fitted to the pooled data and used to estimate the magnitude of the 1 in 3 year wet spells across the UK.

Wind-driven rain is required for buildings standards. It is a major source of moisture in walls. Areas subject to very high levels of wind-driven rain may not be suitable for cavity-wall insulation. Under certain circumstances, cavity-wall insulation can enhance the transfer of moisture through walls to the inside of a building causing mould and damp problems.

Aircraft Icing Potential and Cloud Top Height (CTH) of likely aircraft icing, two UK Met Office (UKMO) experimental satellite products for ICICLE (In-Cloud ICing and Large-drop Experiment) as PNG images. The images are equi-rectangular projections, 800 pixels south to north, 900 pixels west to east, every 30 minutes where data available.

Met Office NWP model data (17km) for use by African National Meteorological & Hydrological Services to carry out their Public Task.

'''DEFINITION'''

Based on daily, global climate sea surface temperature (SST) analyses generated by the European Space Agency (ESA) SST Climate Change Initiative (CCI) and the Copernicus Climate Change Service (C3S) (Merchant et al., 2019; product SST-GLO-SST-L4-REP-OBSERVATIONS-010-024).
Analysis of the data was based on the approach described in Mulet et al. (2018) and is described and discussed in Good et al. (2020). The processing steps applied were: 1. The daily analyses were averaged to create monthly means.
2. A climatology was calculated by averaging the monthly means over the period 1993 - 2014.
3. Monthly anomalies were calculated by differencing the monthly means and the climatology.
4. The time series for each grid cell was passed through the X11 seasonal adjustment procedure, which decomposes a time series into a residual seasonal component, a trend component and errors (e.g., Pezzulli et al., 2005). The trend component is a filtered version of the monthly time series. 5. The slope of the trend component was calculated using a robust method (Sen 1968). The method also calculates the 95% confidence range in the slope.

'''CONTEXT'''

Sea surface temperature (SST) is one of the Essential Climate Variables (ECVs) defined by the Global Climate Observing System (GCOS) as being needed for monitoring and characterising the state of the global climate system (GCOS 2010). It provides insight into the flow of heat into and out of the ocean, into modes of variability in the ocean and atmosphere, can be used to identify features in the ocean such as fronts and upwelling, and knowledge of SST is also required for applications such as ocean and weather prediction (Roquet et al., 2016).

'''CMEMS KEY FINDINGS'''

Warming trends occurred over most of the globe between 1993 and 2021. One of the exceptions is the North Atlantic, which has a region south of Greenland where a cooling trend is found. The cooling in this area has been previously noted as occurring on centennial time scales (IPCC, 2013; Caesar et al., 2018; Sevellee et al., 2017).

'''DOI (product):''' https://doi.org/10.48670/moi-00243

This dataset contains jpg forecast model images from the United Kingdom Meteorological Office collected during the Ice in Clouds Experiment - Tropical (ICE-T) project time period.

Data extracted from the MET Office using the Datapoint API and gives the names, ID codes, elevation (m) and locations of Glasgow's weather stations (lat/long WGS 84). Each station will have different capabilities and the MetOffice Datapoint API's can be used to ascertain which services are available at which station. The MET Office Datapoint API can provide forecast data as well as actual weather observations. The API can extract site specific data which can be presented in a number of formats including text, map overlays and charts. The Met Office provides an API Reference - which is a consolidated guide for using the DataPoint API and its products. A portable document file is also available and icluded with this dataset. The Met Office has a large range of freely available products relating to weather and climate but each user must register to receive an API key. The Met Office Datapoint Terms and Conditions can be examined here. Licence: None datapoint-api-reference.pdf - https://dataservices.open.glasgow.gov.uk/Download/Organisation/494256e0-6740-4597-bc7c-3fd1ba3d46ff/Dataset/231871e4-e2ae-4cc1-a147-ec4f28fd289f/File/9ca1a778-128d-49a6-a044-b078cab70004/Version/cf4ffdeb-3392-45ff-89f2-8dd14390b8be

This dataset contains .png images of the United Kingdom Meteorological Office (UKMO) CAR4 Forecasts collected during the Ice in Clouds Experiment - Tropical (ICE-T) project time period.

Weather Source offers the full European Centre for Medium-Range Weather Forecasts (ECMWF) suite which is known as the best forecast model in the world. The products include (i) historical data back to 2000; (ii) short/mid-range forecast (i.e., up to 360-hour or 15 days); (iii) sub-seasonal forecast out to 46 days (iv) and a seasonal forecast in monthly format out to 7 months. We also offer historical forecasts in pristine format.

In addition, we also have the raw and statistically analyzed ensembles and we summarize the ensemble members by deciles and quartiles which are incredibly valuable to understand the potential of forecast variance (i.e., are the ensemble members tightly wound around the forecast mean which tells me the skill score of the forecast is very high or do they expose a bi-modal distribution which indicates I should plan for possible variance in the forecast.).

Met Office NWP high resolution model data for use by African National Meteorological & Hydrological Services to carry out their Public Task.

Ten operational Numerical Weather Prediction (NWP) and two data assimilation centers are currently contributing analysis/assimilation and forecast model products from global and regional NWP suites, including both operational and reanalysis systems to this component of CEOP. The contributing centers include:

BoM: Bureau of Meteorology CPTEC: Centro de Previsao de Tempo e Estudos Climaticos ECMWF: European Centre for Medium-Range Weather Forecasts ECPC: Experimental Climate Prediction Center EMC: EPSON Meteo Center (Centro EPSON Meteo) GLDAS: Global Land Data Assimilation System GMAO: NASA Global Modeling and Assimilation Office JMA: Japan Meteorological Agency MSC: Meteorological Service Canada NCEP: National Centers for Environmental Prediction NCMRWF: National Center for Medium Range Weather Forecasting UKMO: UK Met Office The Max-Planck Institute for Meteorology (MPIM) in coordination with the ICSU World Data Center for Climate (WDCC) in Hamburg, Germany was designated as the CEOP model output archive center. The WDCC is administered by the Model and Data Group (M&D) at MPIM and the German Climate Computing Center (DKRZ).

To assist with the organization of this activity during the Coordinated Enhanced Observing Period ('CEOP'), a Model Output Management Document was drafted as a guide for the participating centers to use in setting up their processes for meeting their commitments to 'CEOP'. The Guidance Document addressed the two issues of (1) the model output variables requested by 'CEOP' and (2) the two types of requested model output, namely global gridded (in GRIB format) and site-specific Model Output Location Time Series (MOLTS) at each of the 'CEOP' Reference Sites.

A new version of the Guidance Document will be compiled that clarifies what model output data will be generated by the NWP Centers and Groups contributing to the model output component of Coordinated Energy and Water Cycle Observations Project (CEOP) and how they will interface/transfer the data that will be handled and retained at the WDCC. The issues covered in the document will include: (1) global versus regional products; (2) desired assimilation output; Interval and length of free-running forecasts; (3) Operational versus reanalysis data; (4) the CEOP schedule/archive periods; (5) the number and locations of MOLTS sites; and (6) the homogenizing of the model output and metadata formats (i.e. standard parameters).

Results up to this point in the CEOP model output generation effort make it clear that the transfer aspect of the data handling effort has been progressing well. Data from all twelve Centers participating in CEOP have been received at the data archive center and has either been placed into the database at the Hamburg facility, or is in the process of being entered into the database. The current data holdings in the MPIM archive can be viewed http://www.mad.zmaw.de/fileadmin/extern/wdc/ceop/Data_timeline_L_12.pdf.

'''Short Description:'''

The ocean physics reanalysis for the North-West European Shelf is produced using an ocean assimilation model, with tides, at 7 km horizontal resolution.
The ocean model is NEMO (Nucleus for European Modelling of the Ocean), using the 3DVar NEMOVAR system to assimilate observations. These are surface temperature and vertical profiles of temperature and salinity. The model is forced by lateral boundary conditions from the GloSea5, one of the multi-models used by [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=GLOBAL_REANALYSIS_PHY_001_026 GLOBAL_REANALYSIS_PHY_001_026] and at the Baltic boundary by the [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=BALTICSEA_REANALYSIS_PHY_003_011 BALTICSEA_REANALYSIS_PHY_003_011]. The atmospheric forcing is given by the ECMWF ERA5 atmospheric reanalysis. The river discharge is from a daily climatology.

Further details of the model, including the product validation are provided in the [https://documentation.marine.copernicus.eu/QUID/CMEMS-NWS-QUID-004-009.pdf CMEMS-NWS-QUID-004-009].

Products are provided as monthly and daily 25-hour, de-tided, averages. The datasets available are temperature, salinity, horizontal currents, sea level, mixed layer depth, and bottom temperature. Temperature, salinity and currents, as multi-level variables, are interpolated from the model 51 hybrid s-sigma terrain-following system to 24 standard geopotential depths (z-levels). Grid-points near to the model boundaries are masked. The product is updated biannually provinding six-month extension of the time series.

See [https://documentation.marine.copernicus.eu/PUM/CMEMS-NWS-PUM-004-009-011.pdf CMEMS-NWS-PUM-004-009_011] for further details.

'''Associated products:'''

This model is coupled with a biogeochemistry model (ERSEM) available as CMEMS product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_MULTIYEAR_BGC_004_011]. An analysis-forecast product is available from [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_ANALYSISFORECAST_PHY_LR_004_001 NWSHELF_ANALYSISFORECAST_PHY_LR_004_011]. The product is updated biannually provinding six-month extension of the time series.

'''DOI (product) :'''
https://doi.org/10.48670/moi-00059

The Upper Atmosphere Research Satellite (UARS) was the first major element in NASA's Mission to Planet Earth. It was designed to make a systematic study of the stratosphere and provide new data on the mesosphere and thermosphere. The satellite was launched on 12th September 1991.

This dataset contains standard data concerning stratospheric temperature, geopotential height and wind components produced by the upper atmosphere research satellite data assimilation system at the UK Met Office.

The data assimilation system is a development of the scheme used at the Met Office for operational weather forecasting, which has been extended to cover the stratosphere. The primary product is a daily analysis (at 1200 UTC) which is produced using operational observations only. For short periods of particular interest the analyses are available at 6-hourly intervals. Assimilation experiments using UARS (Upper Atmosphere Research Satellite) data in addition to operational meteorological observations have been carried out for limited periods.

'''This product has been archived'''

For operationnal and online products, please visit https://marine.copernicus.eu

'''Short description:'''

The low resolution ocean physics analysis and forecast for the North-West European Shelf is produced using a forecasting ocean assimilation model, with tides, at 7 km horizontal resolution.
The ocean model is NEMO (Nucleus for European Modelling of the Ocean), using the 3DVar NEMOVAR system to assimilate observations. These are surface temperature, vertical profiles of temperature and salinity, and along track satellite sea level anomaly data. The model is forced by lateral boundary conditions from the UK Met Office North Atlantic Ocean forecast model and by the CMEMS Baltic forecast product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=BALTICSEA_ANALYSISFORECAST_PHY_003_006 BALTICSEA_ANALYSISFORECAST_PHY_003_006]. The atmospheric forcing is given by the operational UK Met Office Global Atmospheric model. The river discharge is from a daily climatology. Further details of the model, including the product validation are provided in the [http://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-NWS-QUID-004-001.pdf CMEMS-NWS-QUID-004-001]. Products are provided as hourly instantaneous and daily 25-hour, de-tided, averages. The datasets available are temperature, salinity, horizontal currents, sea level, mixed layer depth, and bottom temperature. Temperature, salinity and currents, as multi-level variables, are interpolated from the model 51 hybrid s-sigma terrain-following system to 24 standard geopotential depths (z-levels). Grid-points near to the model boundaries are masked. The product is updated daily, providing a 6-day forecast and the previous 2-day assimilative hindcast. See [http://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-NWS-PUM-004-001_002.pdf CMEMS-NWS-PUM-004-001_002] for further details.

'''Associated products:'''

This model is coupled with a biogeochemistry model (ERSEM) available as CMEMS product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_ANALYSISFORECAST_BGC_004_002 NWSHELF_ANALYSISFORECAST_BGC_004_002] A reanalysis product is available from: [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_MULTIYEAR_PHY_004_009 NWSHELF_MULTIYEAR_PHY_004_009].

'''DOI (product) :'''
https://doi.org/10.48670/moi-00057

For each forecast run, Weather Source processes all of the forecast ensemble members (31 for GFS and 51 for ECMWF) in real-time and users have the ability to create business intelligence around the spread of the distributions of the ensembles to better understand the potential variances of each forecast which can be very useful for scenario planning but also understand the confidence level in the forecast skill score.